• 한국정보전자통신기술학회논문지
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• 제2권1호
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• pp.73-79
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• 2009

객체지향 프로그래밍 언어를 기반으로 윈도우 사용자의 컴퓨터 파일시스템에 기록된 파일의 의미를 분석한 후, 이를 사용자 편의를 위해 파일명의 의미를 시소러스로 클러스터링 하는 설계를 하고, 파일로 기록된 문자의 의미와 파일확장자를 기반으로, 데이터베이스를 구성하고 참조하여 사용자 작성 파일들을 시소러스의 의미 체계와 통제어로 클러스터링 하여, 윈도우시스템의 화면표시 되는 Icon 파일들을 자동으로 분리하고, 설정하여, Mashup 시각구조로 나타내어 주는 프로세스(WTPM)를 설계하고 구현을 하였다.

• ETRI Journal
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• 제30권3호
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• pp.432-440
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• 2008

In this paper, a user-friendly mobile photo album system and albuming functions to support it are introduced. Stand-alone implementation in a mobile device is considered. The main idea of user-friendly photo browsing for albuming functions is to enable users to organize and browse their photos along semantically meaningful axes of events, personal identities, and categories. Experimental results demonstrate that the proposed method would be sufficiently useful and efficient for browsing personal photos in mobile environment.

• 한국IT서비스학회지
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• 제12권2호
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• pp.335-348
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• 2013

Vessel PMS (Planned Maintenance System) is a paper and/or software based system to monitor vessel engine equipment including main propulsion, steering, auxiliary machinery and cargo handling information. This is one of mandatory survey for vessel introduced by IMO (International Maritime Organization). The planned maintenance as well as documentation must be performed according to a system to be approved by classification agencies. Recently, vessel owners have preferred software based systems to collect and preserve accurate data. However, not ship specific and not taking into account the user are said by end users as operational difficulties. To relieve these concerns, this research analyzes vessel PMS data, suggests a middleware to support automatic collection and design consideration of user interface.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.352-361
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• 1998

The post-processing modules are parts of an integrated system for reinforced concrete structures. This modules are composed of two modules: member design module and calculation report module. The purpose of this paper is to develope modules that increase efficiency and usefulness of an integrated system used reinforced concrete structures design. The development of post-processing modules is necessary for user to design reinforced concrete structures conveniently and quickly. This modules are connected with central database for the benefit of storing amount of input/output data and being used system with little effort. Post-processing modules used Object-Oriented concepts and techniques include identity, classification, polymorphism, and inheritance. Member design module automatically converts no good members into satisfied members by changing section size or reinforcement bar arrangement. This module can be operated both independent member design modules with user input and a part of integrated system with database input. If user operates member design module, calculation report module is created automatically.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.248-249
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• 2022

본 논문에서는 RGB-D 카메라를 이용하여 획득한 다중 사용자의 정보를 기반으로 대상을 구분 및 추적하는 기법을 제안한다. RGB-D 카메라를 통해 획득한 3차원 정보와 색상 정보를 획득하여 각 사용자에 대한 정보를 저장한다. 전체 영상에서 획득한 각 사용자의 위치와 외형에 대한 정보를 통해 현재 프레임과 이전 프레임에서의 사용자간 유사도를 계산하여 전체 영상에서의 사용자 구분 및 위치 추적 알고리즘을 제안한다.

• Asia pacific journal of information systems
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• 제17권4호
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• 정보화정책
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• 제24권2호
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• pp.20-42
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• 2017

본 논문은 인터넷 뱅킹 서비스의 안전성을 평가하기 위한 보안위협을 분류하고 보안 요구사항을 제안하는데 그 목적이 있다. 분류한 보안위협은 기존에 발생하였던, 그리고 발생이 가능한 보안위협을 기반으로 분석하였으며, 이를 통하여 보안 요구사항을 제안하기 위한 기반을 다질 것으로 사료된다. 보안위협 도출을 위하여 인터넷 뱅킹 서비스의 구조를 금융기관 구간과 네트워크 구간, 사용자 구간으로 분류하였으며, 각 구간에서 발생하는 보안위협을 도출하였다. 특히, 사용자 구간이 상대적으로 취약하기 때문에 전체 서비스의 안전성을 확보하기 어려운 상황이므로 이를 중점적으로 분석하였다. 분석한 보안위협을 토대로 안전한 인터넷 뱅킹 서비스를 구성할 수 있을 것으로 예상된다.

• 정보관리학회지
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• 제21권4호
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• pp.251-263
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• 2004

질의응답 시스템에서의 질의 분석 과정은 이용자의 자연어 질의 문장에서 질의 의도를 파악하여 그 유형을 분류하고 정답 추출을 위한 정보를 구하는 것이다. 본 연구에서는 복잡한 분류 규칙 집합이나 대용량의 언어 지식 자원 대신 이용자 질의 문장에서 질의 초점 어휘를 추출하고 구문 구조적으로 관련된 단어들의 의미 정보에 기반하여 효율적으로 질의 유형을 분류하는 방법을 제안한다. 질의 초점 어휘가 생략된 경우의 처리와 동의어와 접미사 정보를 이용하여 질의 유형 분류 성능을 향상시킬 수 있는 방법도 제안한다.

• 한국컴퓨터그래픽스학회논문지
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• 제8권1호
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• pp.1-11
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• 2002

볼륨 렌더링 기술이 실제 응용 분야에서 널리 사용되기 위해서는 사용자가 3차원 데이터에 내재되어 있는 의미있는 정보를 쉽게 찾을 수 있도록 대화식으로 분류 파라미터를 조절하고 그 결과 영상을 빠른 속도로 가시화시켜 주는 것이 필요하다. 이제까지 제시된 볼륨 렌더링의 가속화 방법은 전처리 과정으로 비균등한 볼륨 데이터를 균등한 볼륨으로 재구성하고 분류 작업을 수행한 후, 실행시간에 렌더링을 빠르게 수행하는데 주안점을 두고 있다. 그러나 이러한 방법은 전처리 시간이 길어지고 사용자가 실행시간에 대화식으로 분류 파라미터를 지정하여 그 결과 영상을 피이드백 받을 수 없는 단점이 있다. 본 논문에서는 별도의 하드웨어 없이 범용 컴퓨터 상에서 대화식으로 분류 및 렌더링을 수행할 수 있는 가시화 방법을 제안한다.